Lipid-Reduction Variability and Antidrug-Antibody Formation with Bococizumab
Bibliographic record
Abstract
BACKGROUND: Bococizumab, a humanized monoclonal antibody targeting proprotein convertase subtilisin-kexin type 9 (PCSK9), reduces levels of low-density lipoprotein (LDL) cholesterol. However, the variability and durability of this effect are uncertain. METHODS: We conducted six parallel, multinational lipid-lowering trials enrolling 4300 patients with hyperlipidemia who were randomly assigned to receive 150 mg of bococizumab or placebo subcutaneously every 2 weeks and who were followed for up to 12 months; 96% were receiving statin therapy at the time of enrollment. The patients were assessed for lipid changes over time, stratified according to the presence or absence of antidrug antibodies detected during the treatment period. RESULTS: At 12 weeks, patients who received bococizumab had a reduction of 54.2% in the LDL cholesterol level from baseline, as compared with an increase of 1.0% among those who received placebo (absolute between-group difference, -55.2 percentage points). Significant between-group differences were also observed in total cholesterol, non-high-density lipoprotein cholesterol, apolipoprotein B, and lipoprotein(a) (P<0.001 for all comparisons). However, high-titer antidrug antibodies developed in a substantial proportion of the patients who received bococizumab, which markedly diminished the magnitude and durability of the reduction in LDL cholesterol levels. In addition, among patients with no antidrug antibodies, there was wide variability in the reduction in LDL cholesterol levels at both 12 weeks and 52 weeks. Major cardiovascular events occurred in 57 patients (2.5%) who received bococizumab and in 55 (2.7%) who received placebo (hazard ratio, 0.96; 95% confidence interval, 0.66 to 1.39; P=0.83). The most common adverse event among patients who received bococizumab was injection-site reaction (12.7 per 100 person-years). CONCLUSIONS: In six multinational trials evaluating bococizumab, antidrug antibodies developed in a large proportion of the patients and significantly attenuated the lowering of LDL cholesterol levels. Wide variation in the relative reduction in cholesterol levels was also observed among patients in whom antidrug antibodies did not develop. (Funded by Pfizer; SPIRE ClinicalTrials.gov numbers, NCT01968954 , NCT01968967 , NCT01968980 , NCT02100514 , NCT02135029 , and NCT02458287 .).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".